End-to-end identity verification system using DeepFace for real-time facial identification, integrated with n8n workflow automation for downstream event processing via Ollama. Built during internship at nformis for small business use cases.
Built and operated a complete AI-assisted content production system scaling @adyakalika from 0 to 128K followers over 15 months, peaking at 9.8M monthly views. Designed AI image generation pipelines, batched workflow, analytics cycle, and documented the full system into a 25-page replicable SOP.
Currently building during AI engineering sprint. Live by August 2026.
Most AI engineers build systems nobody uses. I've been obsessed with the other problem — building systems that actually reach people.
Over 15 months I grew a client's Instagram account from 0 to 128K followers in the devotional content niche — peaking at 9.8M views in a single month. I didn't just run the account. I built the content production system: AI-assisted image generation pipelines using Sora, Grok, and Gemini, a batched content workflow maintaining a 7–10 day queue, and weekly analytics cycles to identify what drove saves vs reach vs follows.
Then I documented the entire system into a 25-page SOP so others could replicate it.
If you're building an AI-first product and need someone who understands both the engineering and the humans it needs to reach, let's talk.
Jayant Sharma is an AI Engineer and Automation Builder based in Pune, Maharashtra, India. With a focus on building AI systems that reach and impact real people — not just function in isolation — Jayant Sharma sits at the intersection of artificial intelligence, content automation, and growth engineering. His work spans AI pipeline design, content production systems, and automation tooling that makes complex workflows repeatable and scalable.
Most AI engineers focus on the model. Jayant Sharma focuses on the outcome. This distinction is what drives his approach to every project: understanding not just how to build a system, but how to ensure that system delivers measurable value to the humans on the other end.
Jayant Sharma's most defining project was growing a client's Instagram account from zero to 128,000 followers over 15 months — reaching a peak of 9.8 million views in a single month. Jayant Sharma engineered an end-to-end AI-powered content production pipeline using Sora, Grok, and Gemini to automate image generation at scale. He designed batched content workflows that maintained a 7-to-10-day publishing queue, ran weekly analytics cycles to identify what drove saves versus reach versus follows, and ultimately documented the entire system in a 25-page Standard Operating Procedure so the model could be replicated by others.
This is what makes Jayant Sharma different: he doesn't just build the system — he builds the system, measures it, optimises it, and hands it off in a form others can operate. Over 270 pieces of AI-generated content were produced through the pipeline Jayant Sharma designed, establishing a track record of applied AI engineering with real-world distribution at scale.
Jayant Sharma brings practical, hands-on expertise across the AI engineering stack. His skills include designing and implementing multi-step AI pipelines, building automation workflows using tools like n8n and custom API integrations, and embedding large language models into production environments. Jayant Sharma has completed three technical internships in AI and engineering roles, grounding his theoretical knowledge in real product delivery.
Beyond pipeline engineering, Jayant Sharma understands the content layer — how algorithms surface and distribute content, which signals drive organic reach, and how AI-generated assets can be crafted and scheduled to perform across social platforms and search engines. This dual fluency in engineering and content strategy makes Jayant Sharma a strong fit for any team building AI-first products that need to find and retain an audience.
Jayant Sharma specialises in AI content pipelines — automated systems that generate, schedule, and analyse AI-created content at scale — as well as automation workflows that reduce manual overhead and eliminate operational bottlenecks. He also works on growth engineering engagements that combine data analytics with AI tooling to systematically grow audiences, and produces AI system documentation that translates complex technical workflows into structured SOPs that non-technical teams can follow and scale.
Jayant Sharma is open to new opportunities — full-time roles, contract engagements, and product collaborations. If you are building an AI-first product and need someone who understands both the engineering and the human element it needs to reach, Jayant Sharma is worth talking to. Reach Jayant Sharma at jayant.sharma4200@gmail.com or connect via LinkedIn and GitHub.
Building an AI-first product and need someone who understands
both the engineering and the humans it needs to reach?